Defining Simulation Intent

SIMULATION INTENT

INTRODUCTION

  • Simulation Intent captures from the outset of the design process how the component is to be idealised and represented in the simulation model
  • In this work the thin-sheet and long-slender regions are identified and subdivided out of an aerospace component
  • Depending on the simulation intent defined, different meshing strategies can be used to create efficient meshes for the subdivided model

MODEL PARTITIONING USING GEOMETRIC REASONING

    • The CADfix Thin-Thick tool is used to identify and extract thin-sheet regions from the model.
    • QUB algorithms then use the CADfix API to extract long-slender regions.
    • The remaining regions are classed as ‘Complex’.

       
     

 SIMULATION INTENT 1 : USE A REDUCED DIMENSIONAL MESH, WITH ELEMENT TYPE MATCHED TO GEOMETRIC SHAPE

    • Idealisation automated in Siemens NX
    • Interface data from a cellular model used to automatically tie different regions together

 

SIMULATION INTENT 2: USE A SOLID MESH, WITH ELEMENT SHAPE MATCHED TO GEOMETRIC SHAPE

 

       

CONCLUSIONS

  • Geometric reasoning has been used to subdivide aerospace components based on shape
  • Simulation intent has been used to define different mesh styles for subdivided regions 

 

To view a video of Simulation Intent being used to create a shell-beam mesh of the above aero engine component, please click below.

  Simulation Intent Meshing Demo

MANAGING EQUIVALENT REPRESENTATIONS OF DESIGN AND ANALYSIS MODELS

INTRODUCTION

With simulation based design being used to create superior products in less time and at lower cost it is essential that the analysis tools employed are completely integrated in the design process. This is emphasised by the fact many companies use multiple analysis tools to get access to different specialist functionality. However, with CAD and CAE tools being developed independently of one another, different analysis and design representations are required. For example, an FEA model requires an abstracted version of the design geometry. In this work, three core technologies, namely Cellular Modelling, Virtual Topology and Equivalencing are used to integrate analysis and design models.

CELLULAR MODELLING

Cells in a non-manifold cellular model have specific simulation significance:

•Design space is split into cells representing both solid and fluid domains.
•Automated simplification tools decompose complicated geometry into more meshable sub-regions.
•Non-manifold cellular models are used to calculate interfaces between interacting cells.
  

VIRTUAL TOPOLOGY

Virtual Topology simplifies geometry for analysis purposes without modifying the original geometric model. In this work:

•Virtual topology is used to link cells in cellular decomposition back to the original geometry.
•Virtual Topology is stored in an open structure unlike many CAE systems. This enables analysis attributes to be transferred between systems.

EQUIVALENCING

Throughout the design evolution models of various levels of fidelity are required for different applications. In this work the link between these equivalent representations are identified and stored.

For example a given cell in a solid model may be represented as a 3D solid, 3D solid with small features suppressed, 3D mesh or mesh of 2D shell elements with a thickness attribute for a thin-sheet region. 

Separate data structure

The non-manifold topology of the cellular model is stored in a separate data structure (relational database) along with virtual topology and equivalencing information.

This data structure stores topology in a generic format allowing it to be accessed by and interact with multiple CAD and CAE packages.

Pre-built queries allow interfaces to be found and the topology interrogated for the database environment.  

Integrated design process

CONCLUSION

Automated tools have been developed allowing multiple CAD and CAE tools, e.g. Parasolid, NX, Abaqus, CADFix to interact with one another so that analysis models and attributes can be transferred between packages without any loss of integrity. These analysis attributes can also be transferred between models of varying fidelity, where adjacencies in lower fidelity models are derived through equivalent relationships in the high level cellular model.